Phase 2 progress - API integration complete.
API Changes:
- Replace date_range (List[str]) with start_date/end_date (str)
- Add automatic end_date defaulting to start_date for single day
- Add date format validation
- Integrate PriceDataManager for on-demand downloads
- Add rate limit handling (trusts provider, no pre-config)
- Validate date ranges with configurable max days (MAX_SIMULATION_DAYS)
New Modules:
- api/date_utils.py - Date validation and expansion utilities
- scripts/migrate_price_data.py - Migration script for merged.jsonl
API Flow:
1. Validate date range (start <= end, max 30 days, not future)
2. Check missing price data coverage
3. Download missing data if AUTO_DOWNLOAD_PRICE_DATA=true
4. Priority-based download (maximize date completion)
5. Create job with available trading dates
6. Graceful handling of partial data (rate limits)
Configuration:
- AUTO_DOWNLOAD_PRICE_DATA (default: true)
- MAX_SIMULATION_DAYS (default: 30)
- No rate limit configuration needed
Still TODO:
- Update tools/price_tools.py to read from database
- Implement simulation run tracking
- Update .env.example
- Comprehensive testing
- Documentation updates
Breaking Changes:
- API request format changed (date_range -> start_date/end_date)
- This completes v0.3.0 preparation
Phase 1 of v0.3.0 date range and on-demand download implementation.
Database changes:
- Add price_data table (OHLCV data, replaces merged.jsonl)
- Add price_data_coverage table (track downloaded date ranges)
- Add simulation_runs table (soft delete support)
- Add simulation_run_id to positions table
- Add comprehensive indexes for new tables
New modules:
- api/price_data_manager.py - Priority-based download manager
- Coverage gap detection
- Smart download prioritization (maximize date completion)
- Rate limit handling with retry logic
- Alpha Vantage integration
Configuration:
- configs/nasdaq100_symbols.json - NASDAQ 100 constituent list
Next steps (not yet implemented):
- Migration script for merged.jsonl -> price_data
- Update API models (start_date/end_date)
- Update tools/price_tools.py to read from database
- Simulation run tracking implementation
- API integration
- Tests and documentation
This is work in progress for the v0.3.0 release.
Makes config_path an internal server detail rather than an API parameter.
Changes:
- Remove config_path from SimulateTriggerRequest
- Add config_path parameter to create_app() with default
- Store in app.state.config_path for internal use
- Update trigger endpoint to use internal config path
- Change missing config error from 400 to 500 (server error)
API calls now only need to specify date_range (and optionally models):
POST /simulate/trigger
{"date_range": ["2025-01-16"]}
The server uses configs/default_config.json by default.
This simplifies the API and hides implementation details from clients.
Changed the API to respect the 'enabled' field in model configurations,
rather than requiring models to be explicitly specified in API requests.
Changes:
- Make 'models' parameter optional in POST /simulate/trigger
- If models not provided, read config and use enabled models
- If models provided, use as explicit override (for testing)
- Raise error if no enabled models found and none specified
- Update response message to show model count
Behavior:
- Default: Only runs models with "enabled": true in config
- Override: Can still specify models in request for manual testing
- Safety: Prevents accidental execution of disabled/expensive models
Example before (required):
POST /simulate/trigger
{"config_path": "...", "date_range": [...], "models": ["gpt-4"]}
Example after (optional):
POST /simulate/trigger
{"config_path": "...", "date_range": [...]}
# Uses models where enabled: true
This makes the config file the source of truth for which models
should run, while still allowing ad-hoc overrides for testing.
